Institute for Retailing & Data Science
| Date | Time | Room | Topics | Slides | Readings |
|---|---|---|---|---|---|
| 01-09-2023 | 1:00pm - 6:00pm | LC.2.064 | Introduction | Introduction | Lost in Data Translation, R for Data Science |
| 01-11-2023 | 1:00pm - 6:00pm | LC.1.038 | Modelling | Data Science and the Art of Persuasion | |
| 01-16-2023 | 1:00pm - 6:00pm | LC.2.064 | Visualization/Datascience in R | The Psychology behind Data Visualization Techniques | |
| 01-18-2023 | 1:00pm - 6:00pm | LC.2.064 | Review | Causal Pitchfork Visualization | A Crash Course in Good and Bad Controls |
| 01-20-2023 | 1:00pm - 3:30pm | LC.2.064 | Presentations / Exam |
Gain the ability to create & communicate valuable insight from data
R programming skills to help implementation[…] associate “winning” with the effort process itself. That’s the holy grail of dopamine management for success. It won’t make you dull or unhappy; it will make everything easier and more pleasurable […].
Hire as many data scientists as you can find you’ll still be lost without translators to connect analytics with real business value. […] By 2025 Chief Data Officers and their teams function as a business unit with profit-and-loss responsibilities. The unit, in partnership with business teams, is responsible for ideating new ways to use data, developing a holistic enterprise data strategy (and embedding it as part of a business strategy), and incubating new sources of revenue by monetizing data services and data sharing.
The empirics-first approach is not antagonistic to theory but rather can serve as a stepping-stone to theory. The approach lends itself well to today’s data-rich environment, which can reveal novel research questions untethered to theory. […] we argue that [empirics first] has a natural arc that bends more easily back to real-world implications.
Golder et al. (2022)